The transcriptomic footprint of Mytella strigata: de novo transcriptome assembly of a major invasive species.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-03 DOI:10.1038/s41597-025-04559-y
V G Vysakh, Sandhya Sukumaran, Wilson Sebastian, A Gopalakrishnan
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Abstract

Mytella strigata, a potentially invasive species native to South America, is rapidly spreading across various aquatic ecosystems around the globe, posing a threat to native mussels. This study presents the first comprehensive de novo transcriptome assembly of M. strigata. We generated 254 million reads, which were processed and assembled using the Trinity assembler, resulting in 60362 transcripts with an N50 of 1,578 bp and over 93-98% completeness, as confirmed by BUSCO analysis with multiple ortho-datasets. A number of databases were used for functional annotation, including UniProt, KEGG, Reactome, InterPro, and eggNOG. Gene Ontology and pathway analyses identified transcripts associated with key biological processes, including those associated with cell signalling, metabolism, stress responses, cancer pathways, and immune regulation. This dataset enriches the bivalve database by advancing the understanding of the adaptive success and evolutionary resilience of this invasive species. The present study provides a fundamental framework for future research on the ecological and evolutionary impacts of this invasive species.

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赤藓的转录组足迹:一个主要入侵物种的从头转录组组装。
Mytella strigata是一种原产于南美洲的潜在入侵物种,它正在全球各种水生生态系统中迅速蔓延,对本地贻贝构成威胁。这项研究提出了首个全面的从头转录组组装。我们生成了2.54亿个reads,使用Trinity汇编器对其进行处理和组装,得到60362个转录本,N50为1578 bp,完整性超过93-98%,与多个正交数据集的BUSCO分析一致。函数注释使用了多个数据库,包括UniProt、KEGG、Reactome、InterPro和eggNOG。基因本体和通路分析确定了与关键生物过程相关的转录本,包括与细胞信号传导、代谢、应激反应、癌症途径和免疫调节相关的转录本。该数据集通过推进对这种入侵物种的适应成功和进化弹性的理解,丰富了双壳类数据库。本研究为进一步研究该入侵物种的生态和进化影响提供了基础框架。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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